Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues
Abstract Imaging polarimetry methods have proved their suitability to enhance the image contrast between tissues and structures in organic samples, or even to reveal structures hidden in regular intensity images. These methods are nowadays used in a wide range of biological applications, as for the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-23330-6 |
| _version_ | 1798044378883686400 |
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| author | Carla Rodríguez Albert Van Eeckhout Enrique Garcia-Caurel Angel Lizana Juan Campos |
| author_facet | Carla Rodríguez Albert Van Eeckhout Enrique Garcia-Caurel Angel Lizana Juan Campos |
| author_sort | Carla Rodríguez |
| collection | DOAJ |
| description | Abstract Imaging polarimetry methods have proved their suitability to enhance the image contrast between tissues and structures in organic samples, or even to reveal structures hidden in regular intensity images. These methods are nowadays used in a wide range of biological applications, as for the early diagnosis of different pathologies. To include the discriminatory potential of different polarimetric observables in a single image, a suitable strategy reported in literature consists in associating different observables to different color channels, giving rise to pseudo-colored images helping the visualization of different tissues in samples. However, previous reported polarimetric based pseudo-colored images of tissues are mostly based on simple linear combinations of polarimetric observables whose weights are set ad-hoc, and thus, far from optimal approaches. In this framework, we propose the implementation of two pseudo-colored methods. One is based on the Euclidean distances of actual values of pixels and an average value taken over a given region of interest in the considered image. The second method is based on the likelihood for each pixel to belong to a given class. Such classes being defined on the basis of a statistical model that describes the statistical distribution of values of the pixels in the considered image. The methods are experimentally validated on four different biological samples, two of animal origin and two of vegetal origin. Results provide the potential of the methods to be applied in biomedical and botanical applications. |
| first_indexed | 2024-04-11T23:02:50Z |
| format | Article |
| id | doaj.art-9eff5b248a42444bb41ea936adf75025 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T23:02:50Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-9eff5b248a42444bb41ea936adf750252022-12-22T03:58:05ZengNature PortfolioScientific Reports2045-23222022-11-0112111610.1038/s41598-022-23330-6Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissuesCarla Rodríguez0Albert Van Eeckhout1Enrique Garcia-Caurel2Angel Lizana3Juan Campos4Optics Group, Physics Department, Universitat Autònoma de BarcelonaOptics Group, Physics Department, Universitat Autònoma de BarcelonaLPICM, CNRS, Ecole Polytechnique, Institut Polytechnique de ParisOptics Group, Physics Department, Universitat Autònoma de BarcelonaOptics Group, Physics Department, Universitat Autònoma de BarcelonaAbstract Imaging polarimetry methods have proved their suitability to enhance the image contrast between tissues and structures in organic samples, or even to reveal structures hidden in regular intensity images. These methods are nowadays used in a wide range of biological applications, as for the early diagnosis of different pathologies. To include the discriminatory potential of different polarimetric observables in a single image, a suitable strategy reported in literature consists in associating different observables to different color channels, giving rise to pseudo-colored images helping the visualization of different tissues in samples. However, previous reported polarimetric based pseudo-colored images of tissues are mostly based on simple linear combinations of polarimetric observables whose weights are set ad-hoc, and thus, far from optimal approaches. In this framework, we propose the implementation of two pseudo-colored methods. One is based on the Euclidean distances of actual values of pixels and an average value taken over a given region of interest in the considered image. The second method is based on the likelihood for each pixel to belong to a given class. Such classes being defined on the basis of a statistical model that describes the statistical distribution of values of the pixels in the considered image. The methods are experimentally validated on four different biological samples, two of animal origin and two of vegetal origin. Results provide the potential of the methods to be applied in biomedical and botanical applications.https://doi.org/10.1038/s41598-022-23330-6 |
| spellingShingle | Carla Rodríguez Albert Van Eeckhout Enrique Garcia-Caurel Angel Lizana Juan Campos Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues Scientific Reports |
| title | Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues |
| title_full | Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues |
| title_fullStr | Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues |
| title_full_unstemmed | Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues |
| title_short | Automatic pseudo-coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues |
| title_sort | automatic pseudo coloring approaches to improve visual perception and contrast in polarimetric images of biological tissues |
| url | https://doi.org/10.1038/s41598-022-23330-6 |
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